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Dr. Michael Fuhrman is a consulting scientist at RJLG. His expertise is in image and signal processing, microscopy, optics and instrument development, and pattern recognition. A large part of his work has been in the areas of quantitative image analysis and optical instrument development. He has developed methods to automate the analysis and classification of materials based on their chemistry and morphology. Dr. Fuhrman was a part of several large-scale projects. He performed analyses of the origin, spatial distribution, and levels of environmental contamination in the Deutsche Bank building resulting from the World Trade Center collapse. He had daily reports automatically generated as sampling of the building progressed; and he wrote expert reports detailing the original contamination and the results of subsequent remediation efforts. In the aftermath of this project, he analyzed, validated, and compared ambient air data from multiple air monitoring stations during the demolition of a second building impacted by the World Trade Center collapse. These results were reported daily to the EPA and local citizens' groups. Prior to RJLG, Dr. Fuhrman was Director of Engineering at Bonecraft, LLC, where he worked on the development of a system based on the input of stereo x-ray images to enable surgeons to perform minimally invasive surgery. At Tissueinformatics, he developed software to quantitatively measure morphology, geometrical features, and intensity of staining of histologically prepared sections of skin, engineered tissue, liver, kidney, and blood vessels. His experience at AGR International and Alcoa Laboratories included the development of non-contact optical systems at ultraviolet, visible and infrared wavelengths to measure temperature, coating thickness and a variety of product defects. Dr. Fuhrman has 3 patents including U.S. Patent No. 6,993,170: Methods for Quantitative Analysis of Blood Vessel Structure; U.S. Patent No. 6,819,787: Robust Stain Detection and Quantification for Histological Specimens Based on a Physical Model for Stain Absorption; and U.S. Patent No. 6,577,754: Robust Stain Detection and Quantification for Histological Specimens Based on a Physical Model for Stain Absorption. He has published in peer-reviewed literature. | 